We developed a custom-coded algorithm in MATLAB (MathWorks, Natick, MA, USA) to quantify the spatial distribution of peripheral islands of vision. The GVFs of the right and left eyes were analyzed separately. Both eyes of each participant were included in the study, because potential differences in RP severity, lens status, media opacity, macular edema, and other comorbidity factors that were unique to each eye could have potentially contributed to VF findings. Scanned copies of the subjects’ GVFs were aligned to a blank GVF grid centered on fixation using an affine transformation. The affine transformation used control points in the source and target image and a set of translation, rotation, and shear transformations to align both the source and target images to a common coordinate system. This resulted in a set of GVFs that were aligned such that pixel location in each scan corresponded to the same axis and eccentricity for all GVF images. The accuracy of image alignment was evaluated by manually selecting the pixel locations of three predefined points on the grid, located at (0,0), (40,0), and (0,40). Thirty randomly selected aligned GVFs were used for the right and left eyes. For each image, the distances in pixel values of the above predefined grid locations were recorded. The root mean square deviation of the set of pixel locations for each grid location was computed to determine the accuracy of image alignment.